Architect and build a stateful, headless GenAI application for personalized, grounded content creation. Design multi-agent workflows, integrate enterprise platforms and data services, manage application and conversational state, and produce structured JSON and HTML outputs. Lead architecture and technical decisions, establish coding standards, review engineering work, and write production code. Implement RAG, memory, evaluations, observability, streaming, clarification flows, error handling, and reusable outputs such as tables, charts, and citations using AWS, Amazon Bedrock, and AgentCore.
This is a remote position.
Our client, a world leader in biotechnology and life sciences, is looking for a “ Lead GenAI Engineer”.
Location: South San Francisco, CA (Fully Remote)
Job Duration: Long-Term Contract (Possibility Of Extension)
Company Benefits: Medical, Paid Sick Leave, 401 (k)
Seeking a Senior Lead GenAI Engineer to architect and build a stateful, headless GenAI application for personalized and grounded content creation. The role will design multi-agent workflows, integrate enterprise services, manage application and conversational state, and deliver structured JSON/HTML outputs for downstream content platforms.
This is a hands-on engineering role requiring architecture ownership, technical decision-making, and production coding.
- Significant hands-on experience architecting and building production GenAI applications.
- Strong Python or TypeScript development and microservices experience.
- Experience with stateful, multi-turn and multi-agent orchestration.
- Strong API-first architecture and structured contract design experience.
- Experience building headless services that generate structured outputs for downstream applications.
- Experience integrating GenAI applications with enterprise platforms, data services, and content repositories.
- Strong experience with RAG, grounding, application state, memory, evaluations, and production observability.
- Experience building streaming, multi-turn GenAI applications with clarification flows, conversation history, and error handling.
- Experience rendering structured outputs such as tables, charts, citations, and reusable results.
- Ability to define architecture, establish coding standards, make technical decisions, review engineering work, and write production code.
- Strong hands-on experience with AWS, Amazon Bedrock, and AgentCore.
- Content generation, content-as-code, personalization, or marketing technology experience.
- Experience with Workfront, Veeva Vault PromoMats, AEM Assets, or similar enterprise content platforms.
- Experience in commercial pharma or other regulated content environments.
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